Glossary of common terms and concepts used in website and documentation.

Automatic Container Number Recognition

Automatic container number recognition - automatic recognition of ISO 6346 compatible shipping container identification numbers using a video stream or still images.

ACNR

Automatic Container Number Recognition

ACCR

Automatic Container Code Recognition

ANPR

Automatic Number Plate Recognition

Automatic Number Plate Recognition

Automatic Number Plate Recognition is a technology that uses optical character recognition on images to read vehicle registration plates. It can use existing closed-circuit television, road-rule enforcement cameras, or cameras specifically designed for the task. ANPR is used by police forces around the world for law enforcement purposes, including to check if a vehicle is registered or licensed. It is also used for electronic toll collection on pay-per-use roads and as a method of cataloguing the movements of traffic for example by highways agencies.

ALPR

Automatic License Plate Recognition

ALPR

Automatic License Plate Reader

AVI

Automatic Vehicle Identification

API

API (Application Programming Interface) is a set of subroutine definitions, protocols, and tools for building application software. In general terms, it is a set of clearly defined methods of communication between various software components. A good API makes it easier to develop a computer program by providing all the building blocks, which are then put together by the programmer. An API may be for a web-based system, operating system, database system, computer hardware or software library. An API specification can take many forms, but often includes specifications for routines, data structures, object classes, variables or remote calls.

Artificial intelligence

Artificial intelligence is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".

CCTV, video surveillance system

Closed-circuit television (CCTV), also known as video surveillance, is the use of video cameras to transmit a signal to a specific place, on a limited set of monitors. It differs from broadcast television in that the signal is not openly transmitted, though it may employ point to point (P2P), point to multipoint (P2MP), or mesh wired or wireless links. Though almost all video cameras fit this definition, the term is most often applied to those used for surveillance in areas that may need monitoring such as bars, banks, casinos, schools, hotels, airports, hospitals, restaurants, military installations, convenience stores and other areas where security is needed.

Computer vision

Computer vision is the science that aims to give a similar, if not better, capability to a machine or computer. Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. 

Deep learning

Deep learning is the application to learning tasks of artificial neural networks (ANNs) that contain more than one hidden layer. Now deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision and automatic speech recognition (ASR).

Digital image processing

Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and signal distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.

Intlab Auto LPR

Intlab Auto LPR is an SDK for integrating the function for optical recognition of license plates (number plates).

Intlab Auto MMR

Intlab Auto MMR is an SDK for integrating the function for optical recognition of motor vehicle types, brands, and models.

Intlab Coach

Intlab Coach is an SDK for integrating the function for optical recognition of the eight-digit, two-line railroad passenger car (carriage) and mail (post-office) coach identification numbers used in the Commonwealth of Independent States (C.I.S.) and other countries where the wide-gauge (1,520 mm) track is prevalent.

Intlab Container

Intlab Container is an SDK for integrating the function for optical recognition of shipping container identification numbers.

Inltab Recognition Engines

Inltab Recognition Engines is a family of optical recognition engines developed by Intlab to recognize various objects.

Intlab Wagon

Intlab Wagon is an SDK for integrating the function for optical recognition of the eight-digit railcar (railway carriage) numbers used in the Commonwealth of Independent States (C.I.S.) and other countries where the wide-gauge (1,520 mm) track is prevalent. 

Intlab UIC

Intlab UIC is an SDK for integrating the function for optical recognition of the railcar (railway carriage) UIC numbers.

ITS

ITS are advanced applications which, without embodying intelligence as such, aim to provide innovative services relating to different modes of transport and traffic management and enable various users to be better informed and make safer, more coordinated, and 'smarter' use of transport networks. Although ITS may refer to all modes of transport, the directive of the European Union 2010/40/EU, made on the 7 July, 2010, defined ITS as systems in which information and communication technologies are applied in the field of road transport, including infrastructure, vehicles and users, and in traffic management and mobility management, as well as for interfaces with other modes of transport.

Machine learning

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. Example applications include optical character recognition (OCR), learning to rank, and computer vision.

MMR (Make and Model Recognition)

MMR is an automatic recognition of the make and model of the vehicle.

Neural network

Neural network is a mathematical model based on the same organizing and operating principles as a biological neural network, as well as its software or hardware-based implementation. This concept has arisen when studying natural brain processes and trying to simulate them. Later, when learning algorithms were developed, researchers started to use the resulting models for practical purposes: in prediction problems, for image recognition, in management problems, etc.

Object classification

Object classification is assigning semantic labels to an object, is a fundamental problem in computer vision. It can be used as a building block for many other tasks such as localization, detection, and scene parsing.

Object detection

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, cars, wagons or containers) in digital images and videos.

Object recognition

Object recognition is the ability to perceive an object's physical properties (such as shape, colour and texture) and apply semantic attributes to it (such as identifying the object as an apple). This process includes the understanding of its use, previous experience with the object, and how it relates to others. In a given image you have to detect all objects (a restricted class of objects depend on your dataset), Localized them with a bounding box and label that bounding box with a label.

Object tracking

Object tracking is the process of locating a moving object (or multiple objects) over time using a camera. The algorithm analyzes video frames and finds the positions of the moving target objects relative to the frame. The main problem in object tracking is to compare the positions of the target object in a sequence of video frames, especially if the object moves fast for the specific frame rate. Tracking systems usually use an object motion model that describes how the image of the target object changes in case of different motions. Object tracking has a number of practical applications, including security, surveillance, traffic control, video communication, and video compression. 

Optical Character Recognition

Optical Character Recognition - electronic conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text numbers on vehicle license plates, rolling stocks or cargo containers). It is a common method of digitising printed texts so that they can be electronically edited, searched, stored more compactly, displayed on-line, and used in machine processes such as cognitive computing, machine translation, key data and text mining. OCR is a field of research in pattern recognition, artificial intelligence and computer vision.

Precision

Precision is the ratio of the accurately identified objects to the total number of predicted objects (ratio of true positives to true positives plus false positives). Precision is the fraction of relevant instances among all instances produced by the recognition engine. The higher Precision, the fewer false-positive results you get. However, Precision does not tell you how many of the instances retrieved by the recognition engine are correct. 

Radial distortion (optics)

Radial distortion  - most commonly encountered distortions are radially symmetric, or approximately so, arising from the symmetry of a photographic lens. These radial distortions can usually be classified as either barrel distortions or pincushion distortions.

Barrel distortion
In barrel distortion, image magnification decreases with distance from the optical axis. The apparent effect is that of an image which has been mapped around a sphere (or barrel). Fisheye lenses, which take hemispherical views, utilize this type of distortion as a way to map an infinitely wide object plane into a finite image area. In a zoom lens barrel distortion appears in the middle of the lens's focal length range and is worst at the wide-angle end of the range.

Pincushion distortion
In pincushion distortion, image magnification increases with the distance from the optical axis. The visible effect is that lines that do not go through the centre of the image are bowed inwards, towards the centre of the image, like a pincushion.

Mustache distortion
A mixture of both types, sometimes referred to as mustache distortion (moustache distortion) or complex distortion, is less common but not rare. It starts out as barrel distortion close to the image center and gradually turns into pincushion distortion towards the image periphery, making horizontal lines in the top half of the frame look like a handlebar mustache.

Research & Development

Research & Development is an all kinds of research aimed at obtaining new knowledge and using the findings to develop a new product or technology. Research and development (R&D) is exploratory, theoretical, or experimental work aimed at finding out whether it is technically feasible to develop a certain new technological product within a specific timeframe.

Recognition accuracy

Recognition accuracy is a measure for evaluating the recognition quality, which is usually estimated using F-measure: F = 2 * ((Precision * Recall) / (Precision + Recall)). Precision and Recall provide a rather comprehensive characteristic of a recognition engine. When building such systems, you usually have to find the optimal balance between these two metrics. If you try to improve Recall by making your recognition engine more optimistic, Precision will drop due to an increase in the number of false-positive results. If, instead of this, you tweak your recognition engine to make it more pessimistic (for example, by filtering the results more rigorously), you will improve Precision, but Recall will decline due to the rejection of some correct results. 

Recall

Recall is the ratio of the accurately identified objects to the total number of actual objects in the images (ratio of true positives to true positives plus true negatives). Recall (also known as sensitivity) is the fraction of relevant instances that have been retrieved by the recognition engine over total relevant instances. Note that false-positive results do not affect Recall in any way.

Rolling shutter

Rolling shutter is a method of image capture in which a still picture (in a still camera) or each frame of a video (in a video camera) is captured not by taking a snapshot of the entire scene at single instant in time but rather by scanning across the scene rapidly, either vertically or horizontally. In other words, not all parts of the image of the scene are recorded at exactly the same instant. (Though, during playback, the entire image of the scene is displayed at once, as if it represents a single instant in time.) This produces predictable distortions of fast-moving objects or rapid flashes of light. This is in contrast with "global shutter" in which the entire frame is captured at the same instant.

The "rolling shutter" can be either mechanical or electronic. The advantage of this method is that the image sensor can continue to gather photons during the acquisition process, thus effectively increasing sensitivity. It is found on many digital still and video cameras using CMOS sensors. The effect is most noticeable when imaging extreme conditions of motion or the fast flashing of light. While some CMOS sensors use a global shutter, the majority found in the consumer market use a rolling shutter.

CCDs (charge-coupled devices) are alternatives to CMOS sensors, which are generally more sensitive and more expensive. CCD-based cameras often use global shutters, which take a snapshot representing a single instant in time and therefore do not suffer from the motion artifacts caused by rolling shutters. For recognition purposes especially for wagon and container recognition which have moving in horizontal direction using of cameras with global shutter is mandatory at speeds above 5 km/h for getting quality recognition.

SDK (Software development kit)

Software development kit is a set of development tools that allows software developers to create their own applications by using the functionality contained in the SDK, which is available for integration through the SDK’s API. In many cases, an SDK includes some sample code and supporting technical notes or other documentation to help the software developer better understand the primary reference material.

UIC

UIC - The International Union of Railways (UIC) is an international organization that unites national railroad (railway) companies in order to solve rail transport development problems through joint efforts. Today, the UIC has 194 members across 5 continents.

Wagon CIS Number Recognition (Wagon CIS Code Recognition)

Wagon CIS Number Recognition - is a recognition of the rolling stock identification numbers conforming to the standard used in the former Soviet Union countries (1,520 mm / 4 ft 11 27⁄32 in gauge).

Wagon UIC Number Recognition (Wagon UIC Code Recognition)

Wagon CIS Number Recognition - is a recognition of the rolling stock identification numbers conforming to the UIC standard where is used (1,435 mm / 4 ft 8 1/2 in) gauge.


In preparing this glossary, materials from the site https://www.wikipedia.org were used.